fetch
Official MCP reference server that fetches web pages and converts them to markdown for the model. Can reach internal IP addresses, so sandbox it.
Score
85/100
91,237 stars
10,424 forks
A low score is not a verdict on quality. Young and niche tools start low by design. How we calculate scores
The Open Source Drop Lens
By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.
Updated Sep 2026
Fetch hands your AI assistant a URL reader. The model asks for a page, and the server returns it converted to markdown, in chunks the model can page through when the content runs long.
Setup is one uvx mcp-server-fetch entry in your config, or a Docker image. It obeys robots.txt for model-initiated requests unless you pass --ignore-robots-txt, and it takes a custom user agent and a proxy. No API keys, no service fees.
The MCP steering group maintains it as a reference implementation, and its README carries a caution worth reading twice: it can reach local and internal IP addresses. Fine on a laptop. On any network with internal services, sandbox it first.
Cost Breakdown
fully freeFree tier: Free and open source (the project is moving from MIT to Apache 2.0). No API keys and no paid service behind it.
Self-hosted: Runs locally with uvx, pip or Docker. Installing Node.js is optional and switches it to a more robust HTML simplifier.
Paid: None. The only cost is exposure: the server can request local and internal IP addresses, so treat it as a network-capable process.
No service fees. The real cost is risk: it can fetch internal IP addresses, so sandbox it on any network with private services.
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